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import sys
sys.path.append("../../common")

import test_util as tu
import tritonclient.http as httpclient
from tritonclient.utils import *
import numpy as np
import unittest


class EnsembleTest(tu.TestResultCollector):
    def test_ensemble(self):
        model_name = "ensemble"
        shape = [16]
        with httpclient.InferenceServerClient("localhost:8000") as client:
            input_data_0 = np.random.random(shape).astype(np.float32)
            input_data_1 = np.random.random(shape).astype(np.float32)
            inputs = [
                httpclient.InferInput("INPUT0", input_data_0.shape,
                                      np_to_triton_dtype(input_data_0.dtype)),
                httpclient.InferInput("INPUT1", input_data_1.shape,
                                      np_to_triton_dtype(input_data_1.dtype))
            ]
            inputs[0].set_data_from_numpy(input_data_0)
            inputs[1].set_data_from_numpy(input_data_1)
            result = client.infer(model_name, inputs)
            output0 = result.as_numpy('OUTPUT0')
            output1 = result.as_numpy('OUTPUT1')
            self.assertIsNotNone(output0)
            self.assertIsNotNone(output1)

            self.assertTrue(np.allclose(output0, 2 * input_data_0))
            self.assertTrue(np.allclose(output1, 2 * input_data_1))

        model_name = "ensemble_gpu"
        with httpclient.InferenceServerClient("localhost:8000") as client:
            input_data_0 = np.random.random(shape).astype(np.float32)
            input_data_1 = np.random.random(shape).astype(np.float32)
            inputs = [
                httpclient.InferInput("INPUT0", input_data_0.shape,
                                      np_to_triton_dtype(input_data_0.dtype)),
                httpclient.InferInput("INPUT1", input_data_1.shape,
                                      np_to_triton_dtype(input_data_1.dtype))
            ]
            inputs[0].set_data_from_numpy(input_data_0)
            inputs[1].set_data_from_numpy(input_data_1)
            result = client.infer(model_name, inputs)
            output0 = result.as_numpy('OUTPUT0')
            output1 = result.as_numpy('OUTPUT1')
            self.assertIsNotNone(output0)
            self.assertIsNotNone(output1)

            self.assertTrue(np.allclose(output0, 2 * input_data_0))
            self.assertTrue(np.allclose(output1, 2 * input_data_1))

if __name__ == '__main__':
    unittest.main()
